------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  ...\1903 JOP\law_sheriff.log
  log type:  text
 opened on:  12 Mar 2019, 13:25:39

. 
. set seed X695988c5d980ea95a05262517f7cc4c2000445c8

. 
. ologit law_sheriff lawendorse ///
>      saccounty sac_lawendorse ///
>          black black_lawendorse

Iteration 0:   log likelihood = -2514.1232  
Iteration 1:   log likelihood = -2491.4516  
Iteration 2:   log likelihood = -2491.4285  
Iteration 3:   log likelihood = -2491.4285  

Ordered logistic regression                       Number of obs   =       2328
                                                  LR chi2(5)      =      45.39
                                                  Prob > chi2     =     0.0000
Log likelihood = -2491.4285                       Pseudo R2       =     0.0090

----------------------------------------------------------------------------------
     law_sheriff |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------+----------------------------------------------------------------
      lawendorse |   .5671788   .1082294     5.24   0.000     .3550531    .7793046
       saccounty |   .1764915   .1065686     1.66   0.098    -.0323792    .3853621
  sac_lawendorse |   -.186034   .1547384    -1.20   0.229    -.4893156    .1172477
           black |  -.2196356   .1735403    -1.27   0.206    -.5597684    .1204972
black_lawendorse |  -.1570164   .2619856    -0.60   0.549    -.6704988     .356466
-----------------+----------------------------------------------------------------
           /cut1 |  -.8559863   .0785998                     -1.010039   -.7019336
           /cut2 |    .838106   .0785021                      .6842448    .9919673
----------------------------------------------------------------------------------

. 
. estsimp ologit law_sheriff lawendorse ///
>      saccounty sac_lawendorse ///
>          black black_lawendorse

Iteration 0:   log likelihood = -2514.1232
Iteration 1:   log likelihood = -2491.4516
Iteration 2:   log likelihood = -2491.4285

Ordered logit estimates                           Number of obs   =       2328
                                                  LR chi2(5)      =      45.39
                                                  Prob > chi2     =     0.0000
Log likelihood = -2491.4285                       Pseudo R2       =     0.0090

------------------------------------------------------------------------------
 law_sheriff |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  lawendorse |   .5671788   .1082288     5.24   0.000     .3550542    .7793034
   saccounty |   .1764915    .106568     1.66   0.098     -.032378     .385361
sac_lawend~e |   -.186034   .1547376    -1.20   0.229    -.4893141    .1172461
       black |  -.2196356   .1735394    -1.27   0.206    -.5597666    .1204953
black_lawe~e |  -.1570164   .2619842    -0.60   0.549    -.6704961    .3564633
-------------+----------------------------------------------------------------
       _cut1 |  -.8559863   .0785992          (Ancillary parameters)
       _cut2 |    .838106   .0785015 
------------------------------------------------------------------------------

Simulating main parameters.  Please wait....
% of simulations completed: 14% 28% 42% 57% 71% 85% 100% 

Number of simulations  : 1000
Names of new variables : b1 b2 b3 b4 b5 b6 b7

. 
. 
. * Control group, non-Sac
. 
. setx median

. setx lawendorse 0

. simqi, prval(3) genpr(control_pr) listx

You have set the following values for the explanatory variables:

-------------------------------------------
        Variable |    Value     Description
-----------------+-------------------------
           black |         0       median  
black_lawendorse |         0       median  
      lawendorse |         0         0     
  sac_lawendorse |         0       median  
       saccounty |         0       median  
-------------------------------------------


Quantities of interest based on those explanatory values:

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(law_sh~f=3) |   .3028063     .0169571     .2709733    .3373504

Simqi generated the following new variable(s): control_pr

. 
. simqi, fd(prval(3) genpr(lawendorse_fd)) changex(lawendorse 0 1)

First Difference: lawendorse 0 1

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
         dPr(law_sh~f = 3) |   .1303775      .025065     .0816416    .1790563

Simqi generated the following new variable(s): lawendorse_fd

. 
. 
. * Endorsement Treatment group, non-Sac
. 
. setx lawendorse 1

. simqi, prval(3) genpr(lawendorse_pr) listx

You have set the following values for the explanatory variables:

-------------------------------------------
        Variable |    Value     Description
-----------------+-------------------------
           black |         0       median  
black_lawendorse |         0       median  
      lawendorse |         1         1     
  sac_lawendorse |         0       median  
       saccounty |         0       median  
-------------------------------------------


Quantities of interest based on those explanatory values:

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(law_sh~f=3) |   .4331838     .0195714     .3965827    .4728626

Simqi generated the following new variable(s): lawendorse_pr

. 
. 
. * Difference in baseline probabilities
. 
. tabstat control_pr, s(mean sd min p5 p10 p50 p90 p95 max)

    variable |      mean        sd       min        p5       p10       p50       p90       p95       max
-------------+------------------------------------------------------------------------------------------
  control_pr |  .3028063  .0169571  .2598336  .2752472  .2813126  .3019945  .3247577  .3311789  .3576772
--------------------------------------------------------------------------------------------------------

. tabstat lawendorse_pr, s(mean sd min p5 p10 p50 p90 p95 max)

    variable |      mean        sd       min        p5       p10       p50       p90       p95       max
-------------+------------------------------------------------------------------------------------------
lawendorse~r |  .4331838  .0195714  .3805401  .4022825  .4092001  .4329599  .4593594  .4664347  .4876032
--------------------------------------------------------------------------------------------------------

. 
. gen dif_con_law_pr = lawendorse_pr - control_pr
(1759 missing values generated)

. 
. tabstat dif_con_law_pr, s(mean sd min p5 p10 p50 p90 p95 max)

    variable |      mean        sd       min        p5       p10       p50       p90       p95       max
-------------+------------------------------------------------------------------------------------------
dif_con_la~r |  .1303775   .025065  .0599073   .087927  .0979255  .1301697  .1624466  .1715757  .1940218
--------------------------------------------------------------------------------------------------------

. 
. 
. * Control group, Sac
. 
. setx median

. setx saccounty 1

. setx lawendorse 0

. simqi, prval(3) genpr(sac_control_pr) listx

You have set the following values for the explanatory variables:

-------------------------------------------
        Variable |    Value     Description
-----------------+-------------------------
           black |         0       median  
black_lawendorse |         0       median  
      lawendorse |         0         0     
  sac_lawendorse |         0       median  
       saccounty |         1         1     
-------------------------------------------


Quantities of interest based on those explanatory values:

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(law_sh~f=3) |   .3411456     .0189238     .3028638    .3799418

Simqi generated the following new variable(s): sac_control_pr

. 
. simqi, fd(prval(3) genpr(sac_lawendorse_fd)) changex(lawendorse 0 1 sac_lawendorse 0 1)

First Difference: lawendorse 0 1 sac_lawendorse 0 1

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
         dPr(law_sh~f = 3) |   .0904891     .0268522      .037654    .1420472

Simqi generated the following new variable(s): sac_lawendorse_fd

. 
. 
. * Endorsement Treatment group, Sac
. 
. setx lawendorse 1

. setx sac_lawendorse 1

. simqi, prval(3) genpr(sac_lawendorse_pr) listx

You have set the following values for the explanatory variables:

-------------------------------------------
        Variable |    Value     Description
-----------------+-------------------------
           black |         0       median  
black_lawendorse |         0       median  
      lawendorse |         1         1     
  sac_lawendorse |         1         1     
       saccounty |         1         1     
-------------------------------------------


Quantities of interest based on those explanatory values:

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(law_sh~f=3) |   .4316347     .0198262     .3926154    .4691081

Simqi generated the following new variable(s): sac_lawendorse_pr

. 
. 
. * Difference in baseline probabilities
. 
. tabstat sac_control_pr, s(mean sd min p5 p10 p50 p90 p95 max)

    variable |      mean        sd       min        p5       p10       p50       p90       p95       max
-------------+------------------------------------------------------------------------------------------
sac_contro~r |  .3411456  .0189238  .2865953  .3100647  .3172938    .34066  .3655267  .3733341  .4183505
--------------------------------------------------------------------------------------------------------

. tabstat sac_lawendorse_pr, s(mean sd min p5 p10 p50 p90 p95 max)

    variable |      mean        sd       min        p5       p10       p50       p90       p95       max
-------------+------------------------------------------------------------------------------------------
sac_lawend~r |  .4316347  .0198262  .3630698  .3976055  .4051312  .4324351  .4564387  .4626277  .4873531
--------------------------------------------------------------------------------------------------------

. 
. gen dif_sac_con_law_pr = sac_lawendorse_pr - sac_control_pr
(1759 missing values generated)

. 
. tabstat dif_sac_con_law_pr, s(mean sd min p5 p10 p50 p90 p95 max)

    variable |      mean        sd       min        p5       p10       p50       p90       p95       max
-------------+------------------------------------------------------------------------------------------
dif_sac_co~r |  .0904891  .0268522  -.028206  .0460934  .0550592  .0902742  .1244891  .1338658   .176583
--------------------------------------------------------------------------------------------------------

. 
. 
. * Control group, Black
. 
. setx median

. setx black 1

. setx lawendorse 0

. simqi, prval(3) genpr(black_control_pr) listx

You have set the following values for the explanatory variables:

-------------------------------------------
        Variable |    Value     Description
-----------------+-------------------------
           black |         1         1     
black_lawendorse |         0       median  
      lawendorse |         0         0     
  sac_lawendorse |         0       median  
       saccounty |         0       median  
-------------------------------------------


Quantities of interest based on those explanatory values:

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(law_sh~f=3) |   .2589338     .0328598     .1991802    .3284348

Simqi generated the following new variable(s): black_control_pr

. 
. simqi, fd(prval(3) genpr(black_lawendorse_fd)) changex(lawendorse 0 1 black_lawendorse 0 1)

First Difference: lawendorse 0 1 black_lawendorse 0 1

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
         dPr(law_sh~f = 3) |    .085759     .0541465    -.0232268    .1922942

Simqi generated the following new variable(s): black_lawendorse_fd

. 
. 
. * Endorsement Treatment group, Sac
. 
. setx lawendorse 1

. setx black_lawendorse 1

. simqi, prval(3) genpr(black_lawendorse_pr) listx

You have set the following values for the explanatory variables:

-------------------------------------------
        Variable |    Value     Description
-----------------+-------------------------
           black |         1         1     
black_lawendorse |         1         1     
      lawendorse |         1         1     
  sac_lawendorse |         0       median  
       saccounty |         0       median  
-------------------------------------------


Quantities of interest based on those explanatory values:

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(law_sh~f=3) |   .3446928     .0427983       .26115    .4332344

Simqi generated the following new variable(s): black_lawendorse_pr

. 
. 
. * Difference in baseline probabilities
. 
. tabstat black_control_pr, s(mean sd min p5 p10 p50 p90 p95 max)

    variable |      mean        sd       min        p5       p10       p50       p90       p95       max
-------------+------------------------------------------------------------------------------------------
black_cont~r |  .2589338  .0328598  .1605404  .2070812  .2182256  .2567973  .3027272  .3176737  .3732113
--------------------------------------------------------------------------------------------------------

. tabstat black_lawendorse_pr, s(mean sd min p5 p10 p50 p90 p95 max)

    variable |      mean        sd       min        p5       p10       p50       p90       p95       max
-------------+------------------------------------------------------------------------------------------
black_lawe~r |  .3446928  .0427983   .223279  .2744019  .2908394  .3436391  .4004205  .4156666  .4777667
--------------------------------------------------------------------------------------------------------

. 
. gen dif_black_con_law_pr = black_lawendorse_pr - black_control_pr
(1759 missing values generated)

. 
. tabstat dif_black_con_law_pr, s(mean sd min p5 p10 p50 p90 p95 max)

    variable |      mean        sd       min        p5       p10       p50       p90       p95       max
-------------+------------------------------------------------------------------------------------------
dif_black_~r |   .085759  .0541465 -.0914758 -.0058199  .0174897  .0873611  .1518334  .1759653  .2552377
--------------------------------------------------------------------------------------------------------

. 
. 
. * Calculate difference in first differences
. 
. tabstat lawendorse_fd, s(mean sd min p5 p10 p50 p90 p95 max)

    variable |      mean        sd       min        p5       p10       p50       p90       p95       max
-------------+------------------------------------------------------------------------------------------
lawendorse~d |  .1303775   .025065  .0599073   .087927  .0979255  .1301697  .1624466  .1715757  .1940218
--------------------------------------------------------------------------------------------------------

. tabstat sac_lawendorse_fd, s(mean sd min p5 p10 p50 p90 p95 max)

    variable |      mean        sd       min        p5       p10       p50       p90       p95       max
-------------+------------------------------------------------------------------------------------------
sac_lawend~d |  .0904891  .0268522  -.028206  .0460934  .0550592  .0902742  .1244891  .1338658   .176583
--------------------------------------------------------------------------------------------------------

. tabstat black_lawendorse_fd, s(mean sd min p5 p10 p50 p90 p95 max)

    variable |      mean        sd       min        p5       p10       p50       p90       p95       max
-------------+------------------------------------------------------------------------------------------
black_lawe~d |   .085759  .0541465 -.0914758 -.0058199  .0174897  .0873611  .1518334  .1759653  .2552377
--------------------------------------------------------------------------------------------------------

. 
. gen dif_sac_non_law_fd = sac_lawendorse_fd - lawendorse_fd
(1759 missing values generated)

. gen dif_black_non_law_fd = black_lawendorse_fd - lawendorse_fd
(1759 missing values generated)

. gen dif_black_sac_law_fd = black_lawendorse_fd - sac_lawendorse_fd
(1759 missing values generated)

. 
. tabstat dif_sac_non_law_fd, s(mean sd min p5 p10 p50 p90 p95 max)

    variable |      mean        sd       min        p5       p10       p50       p90       p95       max
-------------+------------------------------------------------------------------------------------------
dif_sac_no~d | -.0398884  .0355547 -.1514957 -.0995733  -.088555 -.0401303  .0051158  .0174281  .0733116
--------------------------------------------------------------------------------------------------------

. tabstat dif_black_non_law_fd, s(mean sd min p5 p10 p50 p90 p95 max)

    variable |      mean        sd       min        p5       p10       p50       p90       p95       max
-------------+------------------------------------------------------------------------------------------
dif_black_n~ | -.0446185  .0551516 -.2140169 -.1365909 -.1174811 -.0435892  .0240937  .0461769  .1465983
--------------------------------------------------------------------------------------------------------

. tabstat dif_black_sac_law_fd, s(mean sd min p5 p10 p50 p90 p95 max)

    variable |      mean        sd       min        p5       p10       p50       p90       p95       max
-------------+------------------------------------------------------------------------------------------
dif~c_law_fd | -.0047301  .0641664 -.2002903 -.1142033 -.0884968 -.0034328  .0764373  .1002386  .1814179
--------------------------------------------------------------------------------------------------------

. 
. 
. drop b1-b7

. drop control_pr-dif_black_sac_law_fd

. 
. log close
      name:  <unnamed>
       log:  ...\1903 JOP\law_sheriff.log
  log type:  text
 closed on:  12 Mar 2019, 13:25:40
------------------------------------------------------------------------------------------------------------
